CN110175957A - Multipotency amount CT sill substance decomposition method - Google Patents
Multipotency amount CT sill substance decomposition method Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 70
- 238000000354 decomposition reaction Methods 0.000 title claims abstract description 39
- 239000000126 substance Substances 0.000 title claims abstract description 32
- 238000013507 mapping Methods 0.000 claims abstract description 40
- 238000013170 computed tomography imaging Methods 0.000 claims abstract description 17
- 238000009826 distribution Methods 0.000 claims description 61
- 238000005314 correlation function Methods 0.000 claims description 19
- 239000000463 material Substances 0.000 claims description 11
- 238000012360 testing method Methods 0.000 claims description 8
- 238000013528 artificial neural network Methods 0.000 claims description 6
- 230000003595 spectral effect Effects 0.000 claims description 6
- 238000004422 calculation algorithm Methods 0.000 claims description 5
- 238000002474 experimental method Methods 0.000 claims description 5
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- 238000004088 simulation Methods 0.000 claims description 4
- 238000002939 conjugate gradient method Methods 0.000 claims description 3
- 239000004744 fabric Substances 0.000 claims description 3
- 238000011478 gradient descent method Methods 0.000 claims description 3
- 239000000758 substrate Substances 0.000 claims description 2
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- 238000003379 elimination reaction Methods 0.000 description 3
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- 230000009977 dual effect Effects 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000003325 tomography Methods 0.000 description 2
- 241000208340 Araliaceae Species 0.000 description 1
- 241000196324 Embryophyta Species 0.000 description 1
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 1
- 235000003140 Panax quinquefolius Nutrition 0.000 description 1
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- 238000002591 computed tomography Methods 0.000 description 1
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- G06T5/70—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/97—Determining parameters from multiple pictures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
Abstract
A kind of multipotency amount CT sill substance decomposition method, comprising: scanned object is placed in multipotency amount CT imaging system, obtains the projection Value Data under N kind energy；Based on the mapping relations pre-established, map the projection Value Data under the N kind energy of scanned object to obtain the data for projection of M kind sill；Wherein, the mapping relations are the M kind sill of different-thickness and projection Value Data and the mapping relations between corresponding M kind sill thickness and scattering strength of the corresponding N kind energy of different scattering strength, and M, N are positive integer, N >=3 and 2≤M≤N-1 or M=N=2；And the data for projection based on M kind sill carries out image reconstruction, obtains the image without artifact.This method is decomposed on M kind sill by that will survey projection Value Data, find the data for projection and scattering strength of the corresponding M kind sill of unknown object structure, since the data for projection of scattering strength and sill separates, good scatter artefacts eradicating efficacy is also achieved.
Description
Technical field
The disclosure belongs to radiography field, is related to a kind of multipotency amount CT sill substance decomposition method.
Background technique
Computer tomography (CT, Computerized Tomography) is using X-ray beam and detector scanning object
The a certain section (tomography) of body is obtained using human organ or the tissue characteristic different to the absorption coefficient of X-ray and reflects this section
The data for projection set of face physically or chemically characteristic, obtains the parameter value of any position on section by Computing, and by
This obtains faultage image.
The main component of CT system includes: x-ray source, detector and rotating device.In CT imaging process, X is penetrated
Line source and detector surround object and do relative rotary motion, obtain the CT data under different rotary angle, also referred to as CT projection with this
Value, in CT imaging, exponential law is obeyed in the decaying of X-ray, and CT projection value is indirect gain, it usually needs " negative logarithm " is pre-
Processing.
Ray scattering is the basic physics challenge for the influence CT picture quality that CT there is since birth, will cause image
The problems such as artifact and inaccurate CT value.
Improve CT imaging performance most crucial problem first is that removing or reducing ray scattering.Remove the method for scattering substantially
Two major classes can be divided into: one kind is hardware based direct scatterometry, for example blocks block/scattering using scattering and block item etc.；
The another kind of scattering estimation for based on algorithm, for example, parsing/Monte Carlo calculations based on physics, projection domain convolutional filtering and
Artifact estimation based on prior image etc..In general, directly measurement class scatter correction method precision is high, but have additionally to hardware
It is required that and generally require rescan, dosage may be increased；And algorithm estimation class method does not have extra demand to hardware, also not
Rescan is needed, but the possible weaker or computation complexity of calibration result dramatically increases.
In recent years, multipotency CT imaging progress is rapid, the power spectrum CT including dual intensity CT and based on photon counting detector.Multipotency
Amount CT sill substance decomposition technique study focuses primarily upon image area method, on alternative manner.There is presently no one kind more
The effective ways of artifact are directly removed in energy CT.
Therefore, the multipotency CT faultage image clearly, without various artifacts under ray scattering in order to obtain, it is necessary to mention
A kind of method effectively removes or reduces image artifacts caused by ray scattering out.
Summary of the invention
(1) technical problems to be solved
It is set forth above at least partly to solve present disclose provides a kind of multipotency amount CT sill substance decomposition method
Technical problem.
(2) technical solution
According to one aspect of the disclosure, a kind of multipotency amount CT sill substance decomposition method is provided, comprising: will be swept
It retouches object to be placed in multipotency amount CT imaging system, obtains the projection Value Data under N kind energy；It is closed based on the mapping pre-established
System, maps the projection Value Data under the N kind energy of scanned object to obtain the data for projection of M kind sill；Wherein, the mapping
Relationship is the M kind sill of different-thickness and projection Value Data under the corresponding N kind energy of different scattering strength and corresponding M kind
The mapping relations of sill thickness and scattering strength, M, N are positive integer, N >=3 and 2≤M≤N-1 or M=N=2；With
And the data for projection based on M kind sill carries out image reconstruction, obtains the image for being free of artifact.
In some embodiments of the present disclosure, the image without artifact includes pseudo- single energy reconstruction image, sill distribution map
One or more of picture and the linear combination of sill distributed image.
In some embodiments of the present disclosure, mapping relations obtain by the following method: utilizing scatter distributions correlation function
Indicate the relationship between the scattering strength under different-energy, as N >=3,2≤M≤N-1, scatter distributions correlation function is not according to
Same multipotency amount CT imaging system carries out calibration test and obtains, and is established by way of simulation or actual experiment in true M
Real projection Value Data under kind of sill and scattering and the mapping relations between corresponding M kind sill thickness and scattering strength.
In some embodiments of the present disclosure, real projection Value Data and corresponding M kind sill thickness and scattering strength it
Between mapping relations in the following way one or more of obtain: look-up table, fitting of a polynomial or artificial neural network.
In some embodiments of the present disclosure, mapping relations obtain by the following method: utilizing scatter distributions correlation function
Indicate the relationship between the scattering strength under different-energy, as M=N=2, scatter distributions correlation function passes through optimal method
Seek optimal scatter distributions solution, to establish two kinds of sills and the difference scattering of different-thickness according to the optimal scatter distributions solution
Projection value under the corresponding two kinds of energy of intensity and the mapping relations between corresponding two kinds of sill thickness and scattering strength.
In some embodiments of the present disclosure, scatter distributions be assumed to be it is smooth, pass through minimize scattering strength TV model
Number (Total Variation Norm) acquires optimal scatter distributions solution；
The algorithm of optimization includes: gradient descent method and conjugate gradient method；
Projection value under two kinds of sills of different-thickness and the corresponding two kinds of energy of different scattering strengths and corresponding M kind base
The one or more of acquisitions of mapping relations in the following way between material thickness and scattering strength: look-up table, multinomial are quasi-
Conjunction or artificial neural network.
In some embodiments of the present disclosure, the data for projection based on M kind sill carries out image reconstruction, obtains pseudo- single energy
Reconstruction image, the method for linear combination of sill distributed image and sill distributed image include: by the projection of M kind sill
Data carry out image reconstruction respectively and obtain the sill distributed image of M kind sill weighting coefficient；List as needed can be worth, and look into
The attenuation coefficient for looking for M kind sill under corresponding energy is added the sill distributed image of the M kind sill weighting coefficient
Power summation, obtaining the puppet list without artifact can reconstruction image；And the needs and different materials attenuation coefficient shown according to image
Changing rule, M kind sill distributed image is made into linear combination, obtains the distributed image of other certain materials.
In some embodiments of the present disclosure, the data for projection based on M kind sill carries out image reconstruction, obtains pseudo- single energy
The method of reconstruction image include: list as needed can value, the attenuation coefficient of M kind sill under corresponding energy is searched, by the M
The data for projection of kind sill is weighted summation, obtains the data for projection of the single energy of puppet without artifact；And by it is pseudo- single can
Data for projection carries out image reconstruction and obtains pseudo- single energy image.
In some embodiments of the present disclosure, the method for carrying out image reconstruction includes parsing image reconstruction and iterative image weight
One kind built or combinations thereof.
In some embodiments of the present disclosure, multipotency amount CT imaging system is a multipotency based on winged focus and energy spectral filter
Measure CT imaging system.
(3) beneficial effect
It can be seen from the above technical proposal that the disclosure provide multipotency amount CT sill substance decomposition method, have with
It is lower the utility model has the advantages that
It 1, will be under different-energy by the scattering strength being added in the power spectrum projection value under multipotency amount under corresponding power spectrum
Relationship between scattering strength is demarcated, and scatter distributions correlation function is obtained, at this time the mapping model by pre-establishing
The weighting coefficient projection value and scatter intensity distribution that two kinds of sills can at least be found out, according to actually measured projection value,
Based on the look-up table or mapping relations pre-established, its projection value can be decomposed on M kind sill, it is unknown to find this
The data for projection and scattering strength of the corresponding M kind sill of object structures, due to the data for projection of scattering strength and M kind sill
It separates, just eliminates the factor of artifact, carry out image reconstruction according only to the data for projection of a variety of sills, can obtain
Image without artifact has the effect of extraordinary elimination artifact.
2, during establishing mapping relations, M kind sill, N kind energy, for N >=3, the case where 2≤M≤N-1,
Scatter distributions correlation function can carry out calibration test according to not homologous ray, defeated to obtain by way of simulation or actual experiment
Enter { { L1, L2, ISc}n, n=1,2,3...N } and output { { P1, P2, P3}n, n=1,2,3...N } between relationship, and by building
Vertical look-up table or the modes such as fitting of a polynomial or artificial neural network obtain biaxial stress structure relationship；For the feelings of M=N=2
Condition, scatter distributions correlation function can seek optimal scatter distributions solution according to optimal method, to establish mapping relations, be applicable in model
It encloses extensively.
Detailed description of the invention
Fig. 1 is to commonly use CT system structure chart and scatter distributions schematic diagram in the prior art.
Fig. 2 is the schematic diagram of the multipotency amount CT sill substance decomposition method according to shown in one embodiment of the disclosure.
Fig. 3 is the flow chart of the multipotency amount CT sill substance decomposition method according to shown in one embodiment of the disclosure.
Fig. 4 is sill thickness and scatter intensity distribution and three kinds of power spectrums different according to shown in one embodiment of the disclosure
Under projection value between mapping relations schematic diagram.
Fig. 5 is that system is imaged in the multipotency amount CT based on winged focal spot techniques and energy spectral filter according to shown in one embodiment of the disclosure
The floor map of system.
Fig. 6 is three energy CT sill substance decomposition methods under the ray scattering according to shown in one embodiment of the disclosure
Effect contrast figure, (a) are the result of direct reconstruction image at medium energies no substantial；It (b) is after carrying out sill decomposition in 70keV
Puppet it is single can reconstruction image result.
Specific embodiment
Fig. 1 is to commonly use CT system structure chart and scatter distributions schematic diagram in the prior art.
Shown in referring to Fig.1, in CT system, scatter distributions enter the data for projection point of detector compared to object is typically inserted through
Cloth, frequency are relatively low, therefore are known as low frequency scatter distributions in figure, and the data for projection for carrying out detector across object is distributed as
The distribution of high frequency main beam, the low frequency scatter distributions cause image artifacts.
The disclosure proposes a kind of multipotency amount CT sill substance decomposition method, by the power spectrum projection value under multipotency amount
The scattering strength under corresponding power spectrum is added, the relationship between the scattering strength under different-energy is demarcated, obtains scattering point
Cloth correlation function can at least find out the weighting coefficient projection value of two kinds of sills by the mapping model pre-established at this time
And scatter intensity distribution, according to actually measured projection value, based on the look-up table or biaxial stress structure relationship pre-established,
Its projection value to be decomposed on M kind sill, find the corresponding M kind sill of the unknown object structures data for projection and
Scattering strength just eliminates the factor of artifact, only root since the data for projection of scattering strength and M kind sill separates
Image reconstruction is carried out according to the data for projection of a variety of sills, the image without artifact can be obtained, has extraordinary elimination pseudo-
The effect of shadow.
For the purposes, technical schemes and advantages of the disclosure are more clearly understood, below in conjunction with specific embodiment, and reference
The disclosure is further described in attached drawing.
First embodiment
In first exemplary embodiment of the disclosure, a kind of multipotency amount CT sill substance decomposition method is provided.
Fig. 2 is the schematic diagram of the multipotency amount CT sill substance decomposition method according to shown in one embodiment of the disclosure.Fig. 3 is
According to the flow chart of multipotency amount CT sill substance decomposition method shown in one embodiment of the disclosure.
Referring to shown in Fig. 2 and Fig. 3, the multipotency amount CT sill substance decomposition method of the disclosure, comprising:
Step S101: under the M kind sill and the corresponding N kind energy of different scattering strengths that pre-establish different-thickness
Mapping relations between projection value and corresponding sill thickness and scattering strength, M, N are positive integer, N >=3,2≤M≤N-1,
Or M=N=2；
According to the CT Theory of Projections of the disclosure, in the relationship between power spectrum and projection value under multipotency amount, consider each
Power spectrum Si(E) corresponding scatter intensity distribution under scattering strength under and different power spectrums, the power spectrum under N energy are able to carry out
It is decomposed not higher than N-1 kind sill, N >=3, the corresponding pad value of every kind of sill and equivalent thickness integral are weighted after decomposition
As the projection energy spectrum coefficient under each energy after combination, as main beam is distributed, in addition the item of scattering strength, obtains each
Projection value under energy.
In the present embodiment, example is carried out with M=2, that is, is decomposed into two kinds of sills, the power spectrum { S under multipotency amounti(E), i
=1,2,3... } with projection value { Pi, i=1,2,3... } and relationship is expressed as form:
Wherein, PiIndicate projection value；Si(E) power spectrum under different-energy is indicated, i indicates to obtain power spectrum under different-energy
Number；μ1(E) and μ2It (E) is respectively the corresponding pad value of two kinds of sills；L1And L2It is integrated for two kinds of sill equivalent thickness,
That is weighting coefficient projection value；For in power spectrum Si(E) scattering strength under.
In the disclosure, during establishing mapping relations, by the way that scattering strength associates with projection value, establish more
The equation group of projection value, sill thickness and scattering strength under a energy, and by solving scatter distributions correlation function, realization side
The solution of journey group obtains the mapping relations (form that can be look-up table) of projection value, sill thickness and scattering strength.?
In subsequent step, for unknown object structures, CT test is carried out using same N kind energy, according to actually measured projection value,
Based on the look-up table or biaxial stress structure relationship pre-established, its projection value can be decomposed on M kind sill, find this not
The data for projection and scattering strength of the corresponding M kind sill of the object structures known, due to the projection of scattering strength and M kind sill
Data separate, and just eliminate the factor of artifact, carry out image reconstruction according only to the data for projection of a variety of sills,
Obtain the image without artifact.It includes following image that data for projection based on M kind sill, which carries out the image that image reconstruction obtains,
Type: one or more of pseudo- single energy reconstruction image, sill distributed image and linear combination of sill distributed image.
Based on practical experience it is found that data for projection for including the case where three kinds of power spectrums or three kinds or more power spectrum, scattering
Intensity distribution rather low-frequency can be indicated with the function of a parameter, while the scatter distributions under different-energy are related
Property it is very strong, using scatter distributions correlation function indicate different-energy under scattering strength between relationship, for example, the present embodiment
In, scatter distributions correlation function can be expressed as form:
Wherein, f () is scatter distributions correlation function, can carry out calibration test according to not homologous ray,It indicates
Scattering strength under any two difference power spectrum.Such as simple common CT system, it can be assumed that:
Wherein, | | A-B | |2It indicates two measurements between elements A and B under metric space, is 2 norms of A and B.
Specifically, situation very strong for scatter distributions correlation, for example, the scatter distributions under different power spectrums are identical, then
Value in expression formula (3) is zero.
Based on it is above-mentioned about consider scatter intensity distribution projection value and multipotency amount power spectrum model, can by simulation or
The real projection data and corresponding a variety of sill thickness and scatter strong that the mode of actual experiment is established under true sill
Mapping relations between degree.
In the present embodiment, example is carried out with formula (1), in practical applications if it is under N kind energy, then can at most into
Row N-1 kind sill decomposes (N >=3), and scatter distributions can be carried out with more accurate modeling, i.e. scatter distributions correlation letter
Several expression formulas is not limited to the example of formula (2) or (3), under multidimensional energy power spectrum of the N greater than 3, corresponding scatter distributions
Correlation function includes two or more parameters.For example scatter distributions can be modeled as under four (N=4) energy containing there are two ginsengs
Several functions, and equally it is the decomposition for carrying out two kinds of sills.
Fig. 4 is sill thickness and scatter intensity distribution and three kinds of power spectrums different according to shown in one embodiment of the disclosure
Under projection value between mapping relations schematic diagram.
As shown in figure 4, in the present embodiment, by the two kinds of sills and different scattering strengths point of largely simulating different-thickness
It plants, is obtained in the data for projection of given three kinds of energy time spectrum, or by that can estimate the actual experiment of scatter intensity distribution
The real projection data for designing true two kinds of sill die bodys of different-thickness, i.e., in determining { { L1, L2, ISc}n, n=1,
2,3...N } under input set, N is the power spectrum total number obtained under different-energy, obtains corresponding output and collects { { P1, P2, P3}n, n
=1,2,3...N }, it may then pass through and establish the modes such as look-up table or fitting of a polynomial or artificial neural network, find
Biaxial stress structure relationship between input and output, that is, a variety of sills and the different scattering strengths for pre-establishing different-thickness are corresponding
Multipotency amount under projection value and a variety of sills thickness and scattering strength between mapping relations.
Establish pair of the projection value and scatter intensity distribution under the corresponding multipotency amount power spectrum of a variety of sills of different-thickness
To mapping relations, in one example, following form is expressed as using formula:
Step S111: scanned object is placed in multipotency amount CT imaging system, obtains the projection value number under N kind energy
According to；
Fig. 5 is that system is imaged in the multipotency amount CT based on winged focal spot techniques and energy spectral filter according to shown in one embodiment of the disclosure
The floor map of system.
In step S111, obtain specific scanning system can be it is as shown in Figure 5 based on winged focus and can spectral filter
Multipotency amount CT imaging system or other imaging systems that can obtain CT data for projection under multiple energy.It certainly, should be based on winged
Focus and the multipotency amount CT imaging system of energy spectral filter are the distinctive imaging systems of tool that applicant proposes, in Shen on the same day
Its structure can be discussed in detail in other patent document please, the disclosure does not make emphasis description.
Step S112: based on the mapping relations pre-established, the projection Value Data under the N kind energy of scanned object is reflected
It penetrates to obtain the data for projection of M kind sill and obtains scatter intensity distribution simultaneously；
In the present embodiment, based on the mapping relations pre-established, according to the projection value number under the N kind energy of scanned object
According to { { P1, P2, P3}n, n=1,2,3...N }, it can learn the corresponding thickness of every kind of sill and scattering strength { { L1, L2, ISc}n, n
=1,2,3...N }, scatter intensity distribution is also obtained while obtaining the data for projection of M kind sill, thus by scattering strength
Element paritng open, carry out image reconstruction according only to the data for projection of a variety of sills, the image without artifact can be obtained.
Pass through the data processing of step S112 at this time, it can obtain the more accurate data for projection of removal scattering.
After above-mentioned steps S112, the data for projection based on M kind sill carries out image reconstruction, obtains the figure for being free of artifact
Picture, the image without artifact include the linear combination of pseudo- single energy reconstruction image, sill distributed image and sill distributed image
One or more of.The explanation of specific embodiment is carried out with step S113 and step S114 below.
Step S113: the data for projection of M kind sill is subjected to image reconstruction respectively and obtains M kind sill weighting coefficient
Sill distributed image；
In the present embodiment, the data for projection of M kind sill is carried out image reconstruction and obtains M kind sill adding respectively by M=2
Distributed image (the I of weight coefficient1, I2).The method for carrying out image reconstruction based on data for projection can be using any one in this field
The method of image reconstruction, the disclosure are not construed as limiting.For example, in some embodiments of the present disclosure, the method that carries out image reconstruction
Including parsing image reconstruction and one kind of iterative image reconstruction or combinations thereof.
Step S114: list as needed can be worth, and search the attenuation coefficient of M kind sill under corresponding energy, weighted
The sill distributed image of coefficient is weighted summation, obtains the single energy reconstruction image of puppet finally without artifact.
This step S114 is first to obtain sill distributed image to be weighted summation according further to sill distributed image
It obtains, in other embodiments, can also be other method for reconstructing, for example, the data for projection based on M kind sill carries out
Image reconstruction, obtain it is pseudo- single can reconstruction image method include: list as needed can value, lookup corresponds to M kind substrate under energy
The data for projection of the M kind sill is weighted summation by the attenuation coefficient of material, obtains the projection of the single energy of puppet without artifact
Data；And the data for projection of pseudo- list energy is subjected to image reconstruction and obtains pseudo- single energy image.
In addition, sill distributed image has been obtained in above-mentioned steps S113, the sill distribution map being also based on
The other desired image without artifact is obtained as carrying out linear combination, such as: the needs and different materials shown according to image
M kind sill distributed image is made linear combination, obtains the distribution map of other certain materials by the changing rule of attenuation coefficient
Picture.
Second embodiment
In second exemplary embodiment of the disclosure, a kind of multipotency amount CT sill substance decomposition method is proposed.
During the introduction of above example, N >=3, the corresponding situation of 2≤M≤N-1, the multipotency amount of the disclosure are illustrated
The case where CT sill substance decomposition method can also correspond to M=N=2, i.e., by establishing 2 kinds of sills in 2 kinds of energy power spectrums
Under projection value and the biaxial stress structure relationship of scatter intensity distribution obtain the image without artifact.
Step S101 establishes the processes of mapping relations there are areas in step S101 ' in the present embodiment and one embodiment
Not.Subsequent step is identical as three kinds of energy and three kinds of energy above sill decomposition methods, and it is pseudo- may finally to obtain removal scattering
The puppet of shadow is single can reconstruction image.
In step S101 ', scatter distributions correlation function can seek optimal scatter distributions solution according to optimal method, thus according to
The throwing under the two kinds of sills and the corresponding two kinds of energy of different scattering strengths of different-thickness is established according to the optimal scatter distributions solution
Mapping relations between shadow value and corresponding sill thickness and scattering strength.
In the present embodiment, the relationship of 2 kinds of sills projection values under 2 kinds of energy and scatter intensity distribution is established, is met
Following equation:
At this time due to lacking a condition, { { L cannot be directly established1, L2, ISc}n, n=1,2,3...N } and { { P1, P2}n, n
=1,2,3...N } mapping relations between.In the present embodiment, it can seek to meet the following conditions by optimization problem
Optimal scatter distributions solution:
min||ISc||TV=min ∑k|ISc(k+1)-ISc(k)| (9)
It is that can be minimized its TV norm (Total in smooth hypothesis that conditions above (9), which is built upon scatter distributions,
Variation Norm), certainly in practical applications, corresponding hypothesis can be made to scatter distributions according to not homologous ray.Tool
Body optimization algorithm can be using common gradient descent method, conjugate gradient method etc..It, can be with by way of the above optimization
Mapping relations are established to two kinds of sill decomposition methods of dual energy CT under ray scattering.
In one example, the multipotency amount CT sill substance decomposition method based on the disclosure and existing method have carried out reality
Test comparison.
Fig. 6 is three energy CT sill substance decomposition methods under the ray scattering according to shown in one embodiment of the disclosure
Effect contrast figure, (a) are the result of direct reconstruction image at medium energies no substantial；It (b) is after carrying out sill decomposition in 70keV
Puppet it is single can reconstruction image result.
Existing method directly carries out the CT imaging of test object at medium energies no substantial, and obtained image reconstruction result is as schemed
In 6 shown in (a), as seen from the figure, artifact caused by a large amount of scatterings, hardening etc. is contained in the image which obtains.It is based on
The CT of disclosed method test object is imaged, and sill is determined at 70keV after carrying out sill decomposition using three energy
Attenuation coefficient is simultaneously weighted summation to the distributed image of weighting coefficient, and the single energy reconstruction image of obtained puppet is referring to (b) in Fig. 6
Shown, as seen from the figure, the image that method of disclosure obtains is free of artifact, has extraordinary effect.
In conclusion present disclose provides a kind of multipotency amount CT sill substance decomposition methods, by under multipotency amount
The scattering strength under corresponding power spectrum is added in power spectrum projection value, the relationship between the scattering strength under different-energy is marked
It is fixed, scatter distributions correlation function is obtained, two kinds of sills can at least be found out by the mapping model pre-established at this time
Weighting coefficient projection value and scatter intensity distribution based on the look-up table pre-established or are reflected according to actually measured projection value
Relationship is penetrated, its projection value can be decomposed on M kind sill, the corresponding M kind sill of the unknown object structures is found
Data for projection and scattering strength since the data for projection of scattering strength and M kind sill separates just eliminate artifact
Factor, carry out image reconstruction according only to the data for projection of a variety of sills, the image without artifact can be obtained, had very
The effect of good elimination artifact, and this method is applied widely.
Certainly, the multipotency amount CT sill substance decomposition method of the disclosure further includes other common methods or step, by
Unrelated in place of the main innovation of the same disclosure, which is not described herein again.
In addition, unless specifically described or the step of must sequentially occur, there is no restriction in the above institute for the sequence of above-mentioned steps
Column, and can change or rearrange according to required design.
Particular embodiments described above has carried out further in detail the purpose of the disclosure, technical scheme and beneficial effects
Describe in detail it is bright, it is all it should be understood that be not limited to the disclosure the foregoing is merely the specific embodiment of the disclosure
Within the spirit and principle of the disclosure, any modification, equivalent substitution, improvement and etc. done should be included in the guarantor of the disclosure
Within the scope of shield.
Claims (10)
1. a kind of multipotency amount CT sill substance decomposition method characterized by comprising
Scanned object is placed in multipotency amount CT imaging system, the projection Value Data under N kind energy is obtained；
Based on the mapping relations pre-established, map the projection Value Data under the N kind energy of scanned object to obtain M kind substrate
The data for projection of material；Wherein, which is the M kind sill and the corresponding N kind energy of different scattering strengths of different-thickness
Under projection Value Data and the mapping relations between corresponding M kind sill thickness and scattering strength, M, N are positive integer, N >=3
And 2≤M≤N-1 or M=N=2；And
Data for projection based on M kind sill carries out image reconstruction, obtains the image for being free of artifact.
2. multipotency amount CT sill substance decomposition method according to claim 1, wherein the image packet without artifact
Include one or more of pseudo- single energy reconstruction image, sill distributed image and linear combination of sill distributed image.
3. multipotency amount CT sill substance decomposition method according to claim 1, which is characterized in that the mapping relations are logical
Following method is crossed to obtain:
The relationship between the scattering strength under different-energy is indicated using scatter distributions correlation function, as N >=3,2≤M≤N-1
When, scatter distributions correlation function carries out calibration test according to different multipotency amount CT imaging systems and obtains, by simulation or in fact
The mode of border experiment establishes real projection Value Data and the corresponding M kind sill thickness in true M kind sill and under scattering
And the mapping relations between scattering strength.
4. multipotency amount CT sill substance decomposition method according to claim 3, which is characterized in that the real projection value
The one or more of acquisitions of mapping relations in the following way between data and corresponding M kind sill thickness and scattering strength:
Look-up table, fitting of a polynomial or artificial neural network.
5. multipotency amount CT sill substance decomposition method according to claim 1, which is characterized in that the mapping relations are logical
Following method is crossed to obtain:
The relationship between the scattering strength under different-energy is indicated using scatter distributions correlation function, as M=N=2, scattering point
Cloth correlation function seeks optimal scatter distributions solution by optimal method, to establish different thickness according to the optimal scatter distributions solution
Projection value under two kinds of sills of degree and the corresponding two kinds of energy of different scattering strength and corresponding two kinds of sill thickness and scattered
Penetrate the mapping relations between intensity.
6. multipotency amount CT sill substance decomposition method according to claim 5, which is characterized in that
The scatter distributions be assumed to be it is smooth, pass through minimize scattering strength TV norm (Total Variation Norm)
Acquire optimal scatter distributions solution；
The algorithm of optimization includes: gradient descent method and conjugate gradient method；
Projection value under two kinds of sills of the different-thickness and the corresponding two kinds of energy of different scattering strengths with corresponding two kinds
The one or more of acquisitions of mapping relations in the following way between sill thickness and scattering strength: look-up table, multinomial
Fitting or artificial neural network.
7. multipotency amount CT sill substance decomposition method according to claim 2, which is characterized in that described to be based on M kind base
The data for projection of material carries out image reconstruction, obtains pseudo- single energy reconstruction image, sill distributed image and sill distributed image
The method of linear combination include:
The data for projection of M kind sill is subjected to image reconstruction respectively and obtains the sill distribution map of M kind sill weighting coefficient
Picture；
List as needed can be worth, and search the attenuation coefficient of M kind sill under corresponding energy, and the M kind sill is weighted system
Several sill distributed images are weighted summation, obtain the single energy reconstruction image of puppet without artifact；And
The changing rule of the needs and different materials attenuation coefficient that are shown according to image is made M kind sill distributed image linear
Combination, obtains the distributed image of other certain materials.
8. multipotency amount CT sill substance decomposition method according to claim 2, which is characterized in that described to be based on M kind base
The data for projection of material carries out image reconstruction, and the method for obtaining pseudo- single energy reconstruction image includes:
List as needed can be worth, and the attenuation coefficient of M kind sill under corresponding energy be searched, by the projection of the M kind sill
Data are weighted summation, obtain the data for projection of the single energy of puppet without artifact；And
The data for projection of pseudo- list energy is subjected to image reconstruction and obtains pseudo- single energy image.
9. multipotency amount CT sill substance decomposition method according to claim 1, which is characterized in that carry out image reconstruction
Method includes parsing image reconstruction and one kind of iterative image reconstruction or combinations thereof.
10. multipotency amount CT sill substance decomposition method according to any one of claim 1 to 9, which is characterized in that institute
Stating multipotency amount CT imaging system is a multipotency amount CT imaging system based on winged focus and energy spectral filter.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110544282A (en) * | 2019-08-30 | 2019-12-06 | 清华大学 | three-dimensional multi-energy spectrum CT reconstruction method and equipment based on neural network and storage medium |
| CN110974275A (en) * | 2019-12-17 | 2020-04-10 | 明峰医疗系统股份有限公司 | Device and method for realizing dual-energy scanning by flying focus switching and X-ray filter |
| CN111134710A (en) * | 2020-01-17 | 2020-05-12 | 清华大学 | Multi-energy CT imaging system |
| CN111134709A (en) * | 2020-01-17 | 2020-05-12 | 清华大学 | Multi-energy CT-based material decomposition method |
| CN113281358A (en) * | 2021-06-22 | 2021-08-20 | 清华大学 | Multi-energy X-ray cone-beam CT imaging system and method |
| CN116563413A (en) * | 2023-07-04 | 2023-08-08 | 中国科学院深圳先进技术研究院 | Correction parameter determining method, image reconstructing method, device, equipment and medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050276373A1 (en) * | 2004-05-26 | 2005-12-15 | Zhengrong Ying | Method of and system for adaptive scatter correction in multi-energy computed tomography |
| US20110019798A1 (en) * | 2009-07-23 | 2011-01-27 | Samsung Electronics Co., Ltd. | X-ray imaging apparatus and method for reducing x-ray scattering |
| CN103559699A (en) * | 2013-11-18 | 2014-02-05 | 首都师范大学 | Multi-energy-spectrum CT image reconstruction method based on projection estimation |
| CN104422704A (en) * | 2013-08-21 | 2015-03-18 | 同方威视技术股份有限公司 | Method of decomposing energy spectrum information of X-ray energy spectrum CT and corresponding reconstruction method |
| CN107356615A (en) * | 2016-05-10 | 2017-11-17 | 清华大学 | A kind of method and system for dual-energy x-ray CT |
| CN109146994A (en) * | 2018-09-17 | 2019-01-04 | 南京航空航天大学 | A kind of metal artifacts reduction method towards the imaging of multi-power spectrum X ray CT |
-
2019
- 2019-04-11 CN CN201910291593.4A patent/CN110175957B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050276373A1 (en) * | 2004-05-26 | 2005-12-15 | Zhengrong Ying | Method of and system for adaptive scatter correction in multi-energy computed tomography |
| US20110019798A1 (en) * | 2009-07-23 | 2011-01-27 | Samsung Electronics Co., Ltd. | X-ray imaging apparatus and method for reducing x-ray scattering |
| CN104422704A (en) * | 2013-08-21 | 2015-03-18 | 同方威视技术股份有限公司 | Method of decomposing energy spectrum information of X-ray energy spectrum CT and corresponding reconstruction method |
| CN103559699A (en) * | 2013-11-18 | 2014-02-05 | 首都师范大学 | Multi-energy-spectrum CT image reconstruction method based on projection estimation |
| CN107356615A (en) * | 2016-05-10 | 2017-11-17 | 清华大学 | A kind of method and system for dual-energy x-ray CT |
| CN109146994A (en) * | 2018-09-17 | 2019-01-04 | 南京航空航天大学 | A kind of metal artifacts reduction method towards the imaging of multi-power spectrum X ray CT |
Non-Patent Citations (6)
| Title |
|---|
| FENG, CHUQING ET AL.: "A multi-energy material decomposition method for spectral CT using neural network", 《MEDICAL IMAGING 2018: PHYSICS OF MEDICAL IMAGING》 * |
| WOO-JIN LEE ET AL.: "Material depth reconstruction method of multi-energy X-ray images using neural network", 《34TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE EMBS》 * |
| XIAOYUE GUO ET AL.: "A TV-constrained decomposition method for spectral CT", 《MEDICAL IMAGING 2017: PHYSICS OF MEDICAL IMAGING》 * |
| 冯初晴 等: "能谱 CT 的标定、重建算法与系统", 《中国体视学与图像分析》 * |
| 郝佳 等: "多能谱 X 射线成像技术及其在 CT 中的应用", 《CT 理论与应用研究》 * |
| 陈佩君 等: "基于图像总变分和张量字典的多能谱CT材料识别研究", 《光学学报》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110544282A (en) * | 2019-08-30 | 2019-12-06 | 清华大学 | three-dimensional multi-energy spectrum CT reconstruction method and equipment based on neural network and storage medium |
| CN110544282B (en) * | 2019-08-30 | 2022-03-29 | 清华大学 | Three-dimensional multi-energy spectrum CT reconstruction method and equipment based on neural network and storage medium |
| CN110974275A (en) * | 2019-12-17 | 2020-04-10 | 明峰医疗系统股份有限公司 | Device and method for realizing dual-energy scanning by flying focus switching and X-ray filter |
| CN111134710A (en) * | 2020-01-17 | 2020-05-12 | 清华大学 | Multi-energy CT imaging system |
| CN111134709A (en) * | 2020-01-17 | 2020-05-12 | 清华大学 | Multi-energy CT-based material decomposition method |
| CN111134709B (en) * | 2020-01-17 | 2021-09-14 | 清华大学 | Multi-energy CT-based material decomposition method |
| CN113281358A (en) * | 2021-06-22 | 2021-08-20 | 清华大学 | Multi-energy X-ray cone-beam CT imaging system and method |
| CN113281358B (en) * | 2021-06-22 | 2022-09-23 | 清华大学 | Multi-energy X-ray cone-beam CT imaging system and method |
| CN116563413A (en) * | 2023-07-04 | 2023-08-08 | 中国科学院深圳先进技术研究院 | Correction parameter determining method, image reconstructing method, device, equipment and medium |
| CN116563413B (en) * | 2023-07-04 | 2024-04-09 | 中国科学院深圳先进技术研究院 | Correction parameter determining method, image reconstructing method, device, equipment and medium |
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